ABSTRACT
Aims: Parkinson's disease (PD) and multiple system atrophy (MSA) are neurodegenerative disorders characterized by motor "parkinsonian" symptoms and non-motor symptoms related to autonomic nervous system (ANS) dysfunction. The latter can be quantified with the analysis of Heart Rate Variability (HRVa) and of its complexity. In this study nonlinear (NL) HRV complexity parameters were calculated to assess their predictive accuracy as markers of “disease” useful for early differentiation between PD and MSA in parkinsonian syndromes of uncertain diagnosis. Study Design: Observational study. Place and Duration of Study: Clinical Physiology-Biomagnetism Center, Policlinico A. Gemelli, Rome Italy. Patients enrolled from January 2010 to October 2013. Methodology: 51 patients [25 with “certain” diagnosis of PD, 9 with a “highly probable” diagnosis of MSA and 17 with parkinsonian syndromes of uncertain neurological definition (6 with “undefined parkinsonism” and 11 with “suspected MSA”)] and 40 age-matched healthy control subjects were studied. Short-term NL HRVa was performed during daily activity and during REM/NREM sleep from 24 h ECG recordings. Discriminant analysis (DA) was used to identify which NL HRV parameters (or their combination) were efficient to differentiate between PD and MSA in cases of uncertain diagnosis. Results: Compared with healthy controls, most NL HRV parameters were significantly altered in patients (p<0.05), during both active and passive awakeness and during sleep. Most evident HRV abnormalities were found during active awakeness in MSA. DA of recurrence plot parameters provided the best predictive accuracy (76.5%) for the classification of parkinsonian patients with uncertain diagnosis. Conclusion: NL HRVa is efficient in differentiating MSA from PD and may improve earlier diagnosis in patients with parkinsonian symptoms of uncertain nature, useful to address second level diagnostic steps and to guide more individualized drug treatment.
ABSTRACT
Though prehypertension has recently been considered as a risk factor for cardiovascular accidents, the pathophysiological mechanism that causes the development of prehypertension in normotensive subjects has not been fully elucidated. Therefore, the present study was conducted to assess the sympathovagal imbalance in prehypertensives and normotensives by spectral analysis of heart rate variability (HRV) to understand the nature of change in autonomic balance in this dysfunction. Body mass index (BMI), waist-hip ratio (WHR), basal heart rate (BHR), blood pressure (BP), rate-pressure product (RPP) and spectral indices of HRV such as total power (TP), normalized low frequency power (LFnu), normalized high frequency power (HFnu), ratio of low frequency power to high frequency power (LF-HF ratio), mean heart rate (mean RR), square root of the mean squared differences of successive normal to normal intervals; (RMSSD), the number of interval differences of successive NN intervals greater than 50 ms (NN50) and the proportion derived by dividing NN50 by the total number of NN intervals (pNN50) were assessed in two groups of young subjects: normotensives (n=68) and prehypertensives (n=66). Sympathovagal balance (SVB) was analyzed and correlated with BMI, WHR, BHR, BP and RPP in both the groups. It was observed that autonomic imbalance in prehypertensives was due to increase in both sympathetic activity and vagal inhibition. LF-HF ratio, the sensitive indicator of SVB was significantly correlated with BMI, WHR, BHR, BP and RPP in prehypertensive subjects. It was concluded that vagal inhibition might be important in the critical alteration of sympathovagal balance in the development of prehypertension in young normotensive subjects.